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Information Taxonomy
* 1 , 2
2  Chalmers University of Technology and University of Gothenburg


There is a diversity of different types and kinds of information. To organize this huge collection into a system, it is necessary to classify information with respect to various criteria developing a Multiscale information taxonomy, in which each dimension is an aspect information taxonomy. We construct such a multiscale information taxonomy based on the general theory of information (Burgin, 2003; 2004; 2010) and making use of its principles and technical tools.

It is important to understand that taxonomies are not auxiliary edifices in science but they are also laws of science when scientifically grounded and validated. For instance, the biological taxonomy of Carolous Linnaeus is a law of biology in the same way as Newton’s laws are laws of physics.

Here we follow taxonomic traditions of Linnaeus Carolous Linnaeus and Charles Saunders Peirce in the direction of information science. On the one hand, the results of our research connect new information science and technology with classical science demonstrating intrinsic links between information theory and profound results of Linnaeus. On the other hand, these results show unity in achievements of scientists working in different countries and on different continents such as biological classification of Linnaeus, chemical classification of Mendeleev, semiotic classifications of Peirce, classifications of subatomic particles in contemporary physics and classifications in information science developed here. We begin with a brief exposition of methodological principles of taxonomy construction and then apply these principles to the development of basic information taxonomies. Here we describe only some of them due to the space restrictions.

  1. Principles of taxonomy construction

Having a multiplicity of objects, it is necessary to induce organization because it can help to study, understand and utilize this multiplicity. Organization is achieved by structuration of the multiplicity. An efficient technique of structuration is construction of taxonomies, classifications, typologies and categorizations. Let us consider the process and basic principles of taxonomy construction.

Taking a multiplicity of objects M, a researcher explicates objects’ properties molding aspects or amalgamated features of M. Then the researcher elucidates a criterion for each aspect. This allows us to form a scale for measuring/evaluating each aspect. Such a scale together with the corresponding criterion allows the researcher to build an aspect taxonomy. Combining together all aspect taxonomies, the researcher obtains a multiscale taxonomy of the multiplicity M.

It is important to understand that according to the contemporary methodology of science, there are three types of scientific laws: classificational, equational and implicational laws. Scientists traditionally consider only two latter types as laws of nature although the first type also reflects important regularities in nature and society.

An equational law has the form of an equation, for example, of a differential equation as many laws in physics, e.g., E = mc2, chemistry or economics.

An implicational law has the form of an implication “If A, then B”. For instance, if ∆ABC is a right triangle, then its sides satisfy the equation c2 = a2 + b2. It is a mathematical law called the Pythagorean theorem.

A classificational law has the form of a classification, typology or taxonomy. The biological taxonomy of the great biologist Linnaeus Carolous Linnaeus (1707-1778) and triadic typologies of the great logician Charles Saunders Peirce (1839-1914) are examples of classificational laws.  

In addition, scientific laws can be qualitative and quantitative.

A quantitative law describes relations between quantitative characteristics of definite phenomena. For instance, Newton’s law of motion ma = F is a quantitative law of physics.

A qualitative law describes relations between qualitative characteristics of definite phenomena. For instance, Galilean law of motion “Every body continues its state of rest or of uniform motion in a straight line unless it is compelled to change that state by forces impressed upon it” is a qualitative law of physics. Classificational laws are usually also qualitative laws.

These methodological findings determine a higher scientific status and importance of the groundbreaking Linnaeus’ classification, as well as of the taxonomies constructed in this paper. Namely, this new understanding of scientific laws shows these taxonomies are qualitative laws of information science.

Note that while equational and implicational laws have been acknowledge in science from its very origin, classificational laws acquired their nomological status only recently in the structure-nominative direction of methodology of science.

  1. Three basic taxonomies of information

We begin with the uppermost level of the taxonomic arrangement, which includes a huge diversity of types, kinds, sorts, categories and classes of information. On this level, we build the existential taxonomy

As information is an omnipresent phenomenon (Burgin and Dodig-Crnkovic, 2011), it is crucial to start its classification on the global level of the whole world. This thesis implies the conjecture that the structure of the world affects existence of forms of information, which correspond to this structure. The large-scale structure of the world is represented by the Existential Triad of the World (Burgin, 2012):

  • Physical World
  • Mental World
  • World of Structures

In the Existential Triad, the Physical (material) World is conceived as the physical reality studied by natural sciences, the Mental World encompasses different levels of mentality, and the World of Structures consists of various forms and types of structures.

The existential stratification of the World continues the tradition of Plato with his World of Ideas (Plato, 1961) and the tradition of Charles Sanders Peirce with his extensive triadic classifications (Peirce, 1931-1935).

This stratification brings us to the phenomenon studied by the general theory of information and called information in a broad sense (Burgin, 2010). According to this approach, information in a broad sense is represented in each of the three worlds. In the Physical (material) World, it is called energy supporting in such a way the conjecture of von Weizsäcker that energy might in the end turn out to be information (Weizsäcker, 1974). Situated at the first level of the Mental World, individual mental energy includes psychic energy studied by such psychologists as Ernst Wilhelm von Brücke (1819-1892), Sigmund Freud (1856-1939) and Carl Gustav Jung (1875-1961). Information in a broad sense, which is situated in the World of Structures, is called information in a strict sense.

As a result, we have three types of information in the global existential taxonomy:

  • Physical-world information or energy
  • Mental-world information and its particular case, mental energy
  • Structural-world information or information per se defined as information in a strict sense

We will not analyze here the first two kinds of information in a broad sense as the first of them belongs to the scope of physics, while the second one is in the domain of psychology. Our concern is information in a strict sense or simply information.

The developmental taxonomy is brought on by the temporal aspect of information:

  • Potential information
  • Actualized information
  • Emerging information

Let us consider some examples.

Example 1. Information in a book before somebody reads it is potential.

It is possible to measure potential information by its potential to make changes in the corresponding infological system. For instance, measuring potential epistemic information, we estimate (measure) potential changes in the knowledge system (Burgin, 2011).

Example 2. Information that already gave knowledge about something, e.g., information about observation of a positron obtained by Carl Anderson in 1932, is actualized.

It is possible to measure actual information by changes it made in the corresponding infological system. For instance, measuring actualized epistemic information, we determine (measure) changes in the knowledge system made by reception of this information (Burgin, 2011).

Example 3. Information in a computer, which processes this information or in the head of a person who thinks about it, is emerging.

It is possible to estimate emerging information by its potential to make changes, by transformations it made in the corresponding infological system and by the rate of ongoing transformations. For instance, measuring emerging epistemic information, we estimate (measure) what changes in the knowledge system have already been made and reckon the rate of ongoing changes.

Based on the extended triune model of the brain developed in (Burgin, 2010), we have the following bifocal formation/action taxonomy/typology, in which the first facet reflects the form nature of information existence while the second facet mirrors action category of information existence:

  • Epistemic (form) or cognitive (action) information
  • Instructional (form) or effective (action) information
  • Emotional (form) or affective (action) information

In this taxonomy, the first term/name of each class represents the form of the corresponding infological system, while the second term/name represents action of information. It means that the first nominal attribute of the taxonomic classes characterizes formation aspects of information while the second operational attribute of the taxonomic classes characterizes procedural aspects of information.

  1. Taxonomies suggested by other authors

Banathy (1995) consider three important types of information. With respect to a system R, it is possible to consider referential, non-referential, and state-referential information.

  1. Referential information has meaning in the system R.
  2. Non-referential information has meaning outside the system R, e.g., information that reflects mere observation of R.
  3. State-referential information reflects an external model of the system R, e.g., information that represents R as a state transition system.

Braman (1989) classifies roles of information:

1) information as a resource, coming in pieces unrelated to knowledge or information flows into which it might be organized;

2) information as a commodity is obtained using information production chains, which create and add economic value to information;

3) information as a perception of patterns has past and future, is affected by motive and other environmental factors, and itself has its effects;

4) information as a constitutive force in society, essentially affecting its environment.

All constructed taxonomies together form a hierarchical multiscale information taxonomy, which gives a systematic picture of information.


Banathy, B.A. (1995) The 21st century Janus: The three faces of information, Systems Research, v. 12, No. 4, pp. 319-320

Braman, S. (1989) Defining information: An approach for policymakers, Telecommunications Policty, v. 13, No. 1, pp. 233-242

Burgin, M. Theory of Information: Fundamentality, Diversity and Unification, World Scientific, New York/London/Singapore, 2010

Burgin, M. (2011) Epistemic Information in Stratified M-Spaces, Information, v. 2, No.2, pp. 697 - 726

Burgin, M. Structural Reality, Nova Science Publishers, New York, 2012

Burgin, M. and Dodig-Crnkovic, G. (2011) Information and Computation – Omnipresent and Pervasive, in Information and Computation, World Scientific, New York/London/Singapore, pp. vii – xxxii          

Linnaeus, C. Systema naturae, sive regna tria naturae systematice proposita per classes, ordines, genera, & species, Johann Wilhelm de Groot for Theodor Haak, Leiden, 1735

Peirce C. S. (1931-1935) Collected papers, v. 1-6, Cambridge University Press, Cambridge, England

von Weizsäcker, C.F. Die Einheit der Natur, Deutscher Taschenbuch Verlag, Munich, Germany, 1974